A fully dynamic mixing time‐scale model for the sparse Lagrangian multiple mapping conditioning approach

Abstract

Multiple mapping conditioning / large eddy simulation (MMC-LES) is a promising model for turbulence-chemistry interactions, successfully applied to simulate different combustion regimes involving gaseous, liquid, and solid fuels. MMC-LES attempts to produce accurate molecular mixing by localising mixing in an independent, composition-like reference space. In the MMC mixing model, mixing between two stochastic particles is defined based on the Lagrangian mixing time-scale τL, which is defined as the ratio of the Lagrangian subgrid-scale mixture fraction variance (fL′2˜) and the scalar dissipation rate (χL), typically modelled algebraically, based on fixed values of global constants at all spatial locations. Accurate modelling of τL is essential towards predicting the conditional scalar fluctuations, which is otherwise highly challenging if the same set of static constants are used at all spatial locations for complex flames with varying extinction/re-ignition. Herein, a fully dynamic mixing time-scale model (dyn-aISO) is proposed within the MMC-LES framework, which dynamically evaluates fL′2˜ and χL, essentially based on a local variance coefficient and variable turbulent Schmidt number, respectively, eliminating the need for specifying tuneable model constants. This novel dyn-aISO model is used to simulate the pilot-stabilised Sandia flame series with increasing local extinction levels. The conditional and unconditional profiles of compositional scalars from the new dynamic model are compared with those from a fully static model (st-aISO) and a model which uses a static constant for fL′2˜ (stCf-aISO). Numerical results from different timescale models deviate from each other for Sandia flame F having a high jet Reynolds number. With the proposed improvement of the micro-mixing time-scale model, the dyn-aISO model accurately captures the transient behaviour of the complete flame series, which could otherwise be obtained by the tuning of static constants. The role of molecular and turbulent mass diffusivities, coefficient of residual variance of mixture fraction, mixing distance, and the mixing time-scale on the predictions of the reactive scalars is also explored.